



'''simple docstring'''






def  lowerCamelCase__			(		_A							):
  a		:   Optional[Any]	  =	generate_pascal_triangle(_A							)
  for row_idx in range(_A							):
    # Print left spaces
    for _ in range(num_rows - row_idx - 1							):
      print(end=' '							)
    # Print row values
    for col_idx in range(row_idx + 1							):
      if col_idx != row_idx:
        print(triangle[row_idx][col_idx]					,     end=' '							)
      else:
        print(triangle[row_idx][col_idx]					,     end=''							)
    print()
def  lowerCamelCase__			(		_A							):

  if not isinstance(_A					,     _A							):
    raise TypeError('The input value of \'num_rows\' should be \'int\''							)

  if num_rows == 0:
    return []
  elif num_rows < 0:
    raise ValueError(
        'The input value of \'num_rows\' should be greater than or equal to 0'							)

  a		:   list[list[int]]	  =	[]
  for current_row_idx in range(_A							):
    a		:   int	  =	populate_current_row(_A					,     _A							)
    triangle.append(_A							)
  return triangle
def  lowerCamelCase__			(		_A					,     _A							):
  a		:   Any	  =	[-1] * (current_row_idx + 1)
  # first and last elements of current row are equal to 1
  a  ,      a		:   Union[str, Any]	  =	1, 1
  for current_col_idx in range(1					,     _A							):
    calculate_current_element(
        _A					,     _A					,     _A					,     _A							)
  return current_row
def  lowerCamelCase__			(		_A					,     _A					,     _A					,     _A					,     ):
  a		:   List[Any]	  =	triangle[current_row_idx - 1][current_col_idx - 1]
  a		:   Any	  =	triangle[current_row_idx - 1][current_col_idx]
  a		:   Optional[Any]	  =	above_to_left_elt + above_to_right_elt
def  lowerCamelCase__			(		_A							):

  if not isinstance(_A					,     _A							):
    raise TypeError('The input value of \'num_rows\' should be \'int\''							)

  if num_rows == 0:
    return []
  elif num_rows < 0:
    raise ValueError(
        'The input value of \'num_rows\' should be greater than or equal to 0'							)

  a		:   list[list[int]]	  =	[[1]]

  for row_index in range(1					,     _A							):
    a		:   Union[str, Any]	  =	[0] + result[-1] + [0]
    a		:   int	  =	row_index + 1
    # Calculate the number of distinct elements in a row
    a		:   int	  =	sum(divmod(_A					,     2							)							)
    a		:   Optional[int]	  =	[
        temp_row[i - 1] + temp_row[i] for i in range(1					,     distinct_elements + 1							)
    ]
    a		:   List[str]	  =	row_first_half[: (row_index + 1) // 2]
    row_second_half.reverse()
    a		:   Optional[Any]	  =	row_first_half + row_second_half
    result.append(_A							)

  return result
def  lowerCamelCase__			(		):
  from collections.abc import Callable
  from timeit import timeit

  def benchmark_a_function(_A					,     _A							) -> None:
    a		:   int	  =	f"""{func.__name__}({value})"""
    a		:   Optional[int]	  =	timeit(f"""__main__.{call}"""					,     setup='import __main__'							)
    # print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
    print(f"""{call:38} -- {timing:.4f} seconds"""							)

  for value in range(15							):  # (1, 7, 14):
    for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
      benchmark_a_function(_A					,     _A							)
    print()


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     benchmark()




'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase:   Tuple					=		logging.get_logger(__name__)

lowerCAmelCase:   Any					=		{
    'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       """pegasus"""
    lowercase__					=       ["""past_key_values"""]
    lowercase__					=       {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}







    def __init__( self					:    Union[str, Any]		,     __snake_case					:    Tuple=5_02_65		,     __snake_case					:    List[Any]=10_24		,     __snake_case					:    Optional[Any]=12		,     __snake_case					:    Tuple=40_96		,     __snake_case					:    str=16		,     __snake_case					:    int=12		,     __snake_case					:    Tuple=40_96		,     __snake_case					:    int=16		,     __snake_case					:    Tuple=0.0		,     __snake_case					:    Any=0.0		,     __snake_case					:    Any=True		,     __snake_case					:    Optional[int]=True		,     __snake_case					:    Any="gelu"		,     __snake_case					:    str=10_24		,     __snake_case					:    Dict=0.1		,     __snake_case					:    List[Any]=0.0		,     __snake_case					:    str=0.0		,     __snake_case					:    str=0.02		,     __snake_case					:    Union[str, Any]=0		,     __snake_case					:    List[Any]=False		,     __snake_case					:    Optional[Any]=0		,     __snake_case					:    str=1		,     __snake_case					:    Any=1		,     **__snake_case					:    int		,     ):
      a		:   Optional[int]	  =	vocab_size
      a		:   List[str]	  =	max_position_embeddings
      a		:   List[Any]	  =	d_model
      a		:   Tuple	  =	encoder_ffn_dim
      a		:   List[str]	  =	encoder_layers
      a		:   str	  =	encoder_attention_heads
      a		:   str	  =	decoder_ffn_dim
      a		:   Optional[int]	  =	decoder_layers
      a		:   Optional[int]	  =	decoder_attention_heads
      a		:   Optional[int]	  =	dropout
      a		:   Any	  =	attention_dropout
      a		:   str	  =	activation_dropout
      a		:   List[Any]	  =	activation_function
      a		:   Union[str, Any]	  =	init_std
      a		:   List[Any]	  =	encoder_layerdrop
      a		:   Union[str, Any]	  =	decoder_layerdrop
      a		:   List[Any]	  =	use_cache
      a		:   Any	  =	encoder_layers
      a		:   Optional[int]	  =	scale_embedding  # scale factor will be sqrt(d_model) if True
      super().__init__(
          pad_token_id=__snake_case		,     eos_token_id=__snake_case		,     is_encoder_decoder=__snake_case		,     decoder_start_token_id=__snake_case		,     forced_eos_token_id=__snake_case		,     **__snake_case		,     )







    @property
    def      lowercase_			( self					:    int      ):
      return self.encoder_attention_heads







    @property
    def      lowercase_			( self					:    int      ):
      return self.d_model